Manycore Network Interfaces for In-Memory Rack-Scale Computing

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Spectral algorithms are some of the main tools in optimization and inference problems on graphs. Typically, the graph is encoded as a matrix and eigenvectors and eigenvalues of the matrix are then used to solve the given graph problem. Spectral algorithms ...

Implanted medical devices (IMDs) have been widely developed to support the monitoring and recording of biological data inside the body or brain. Wirelessly powered IMDs, a subset of implantable electronics, have been proposed to eliminate the limitations r ...

Addressing the environmental impact of electronic waste in biomedical sensing, an eco-conscious approach to the realization of a Chitosan-based Acetone sensor tag for wireless gas monitoring is presented. The fabrication involves inkjet printing of silver ...

Driven by the demand for real-time processing and the need to minimize latency in AI algorithms, edge computing has experienced remarkable progress. Decision-making AI applications stand out for their heavy reliance on data-centric operations, predominantl ...

In recent years, there has been a surge of interest in predicting computed activation barriers, to enable the acceleration of the automated exploration of reaction networks. Consequently, various predictive approaches have emerged, ranging from graph-based ...

In the past decades, a significant increase of the transistor density on a chip has led to exponential growth in computational power driven by Moore's law. To overcome the bottleneck of traditional von-Neumann architecture in computational efficiency, effo ...

Embedded memories occupy an increasingly dominant part of the area and power budgets of modern systems-on-chips (SoCs). Multi-ported embedded memories, commonly used by media SoCs and graphical processing units, occupy even more area and consume higher pow ...

We examine the connection of two graph parameters, the size of a minimum feedback arcs set and the acyclic disconnection. A feedback arc set of a directed graph is a subset of arcs such that after deletion the graph becomes acyclic. The acyclic disconnecti ...

Modern hardware is increasingly complex, requiring increasing effort to understand in order to carefully engineer systems for optimal performance and effective utilization. Moreover, established design principles and assumptions are not portable to modern ...

Accessing input data is a critical operation in data analytics: i) slow data access significantly degrades performance, and ii) storing everything in the fastest medium, i.e., memory, incurs high operational and hardware costs. Further, while GPUs offer in ...

Machine learning and data processing algorithms have been thriving in finding ways of processing and classifying information by exploiting the hidden trends of large datasets. Although these emerging computational methods have become successful in today's ...

Graph machine learning offers a powerful framework with natural applications in scientific fields such as chemistry, biology and material sciences. By representing data as a graph, we encode the prior knowledge that the data is composed of a set of entiti ...

Virtual Memory (VM) is a critical programming abstraction that is widely used in various modern computing platforms. With the rise of datacenter computing and birth of planet-scale online services, the semantic and capacity requirements from memory have ev ...

Positron emission tomography is a nuclear imaging technique well known for its use in oncology for cancer diagnosis and staging. A PET scanner is a complex machine which comprises photodetectors placed in a ring configuration that detect gamma photons gen ...

Frequency-bin qubits get the best of time-bin and dual-rail encodings, but require external modulators and pulse shapers to build arbitrary states. Here, instead, the authors work directly on-chip by controlling the interference of biphoton amplitudes gene ...

This thesis demonstrates that it is feasible for systems code to expose a latency interface that describes its latency and related side effects for all inputs, just like the code's semantic interface describes its functionality and related side effects. S ...

We propose ordering-based approaches for learning the maximal ancestral graph (MAG) of a structural equation model (SEM) up to its Markov equivalence class (MEC) in the presence of unobserved variables. Existing ordering-based methods in the literature rec ...

Federated learning is a semi-distributed algorithm, where a server communicates with multiple dispersed clients to learn a global model. The federated architecture is not robust and is sensitive to communication and computational overloads due to its one-m ...

Biochemical reaction rates in microfluidic systems are known to be limited by the diffusional transport of reagents, leading often to lowered sensitivity and/or longer detection times in immunoassays. Several methods, including electrically powering electr ...

Many sports leagues organize their competitions as round-robin tournaments. This tournament design has a rich mathematical structure that has been studied in the literature over the years. We review some of the main properties and fundamental scheduling me ...

Manycore Network Interfaces for In-Memory Rack-Scale Computing

Chattez avec Graph Search

The Power of Two Matrices in Spectral Algorithms for Community Recovery

Integrated Wireless Power, Data Communication, and Thermal Sensing System for Autonomous Multisite Brain Implants

Eco-Conscious Approach to Wireless Gas Monitoring With a Hybrid Printed Passive Sensor Tag

EdgeAI-Aware Design of In-Memory Computing Architectures

Benchmarking machine-readable vectors of chemical reactions on computed activation barriers

Towards Scalable Electronics: Synthetic 2D Materials for Large-Area 2D Circuit Integration

Multi-Ported GC-eDRAM Bitcell with Dynamic Port Configuration and Refresh Mechanism

The connection of the acyclic disconnection and feedback arc sets - On an open problem of Figueroa et al

Chaosity: Understanding Contemporary NUMA-architectures

HetCache: Synergising NVMe Storage and GPU acceleration for Memory-Efficient Analytics

2D Nanosystems: Applications of 2D Semiconductors for In-Memory Computing

Equivariant Neural Architectures for Representing and Generating Graphs

Rebooting Virtual Memory with Midgard

Integrated electronics for time-of-flight positron emission tomography photodetectors

Programmable frequency-bin quantum states in a nano-engineered silicon device

Latency Interfaces for Systems Code

Novel Ordering-based Approaches for Causal Structure Learning in the Presence of Unobserved Variables

Privatized graph federated learning

Efficient AC electrothermal flow (ACET) on-chip for enhanced immunoassays

A tutorial on graph models for scheduling round-robin sports tournaments